Multi-modal sensing with integrated machine learning to differentiate specific leukocytes targeted by electrically...

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Immunodiagnostics

Background:

• Advancements in diagnostic technology are crucial for personalized medicine.
• Current methods struggle with simultaneous analysis of multiple biomarkers, hindering complex disease prognosis.
• There is a need for innovative, non-invasive diagnostic solutions.

Purpose of the Study:

• To develop and validate a multifrequency impedance cytometry apparatus for simultaneous multiplex biomarker analysis.
• To create novel frequency-sensitive barcoded metal oxide Janus particles (MOJPs) for cell-receptor targeting.
• To enable precise classification of immune-specific surface receptors on neutrophils.

Main Methods:

• Fabrication of metal oxide Janus particles (MOJPs) functionalized to target neutrophil surface proteins (CD11b, CD66b).
• Utilizing a multifrequency electric field to modulate MOJPs' electrical properties.
• Employing a multi-modal system with supervised machine learning and high-speed video microscopy for classification based on electrical recordings.

Main Results:

• Achieved high precision and sensitivity (>90% accuracy) in distinguishing neutrophil-MOJP conjugates from cells alone.
• Demonstrated ability to differentiate the number of MOJPs conjugated per cell (>80% accuracy) and across different MOJP types (>75% accuracy).
• Confirmed design robustness and consistency across individual and multiple blood samples.

Conclusions:

• The developed multifrequency impedance cytometry apparatus with MOJPs provides a robust platform for high-precision multiplex biomarker detection.
• This technology has significant potential for improving prognosis in complex diseases by enabling simultaneous analysis of multiple biomarkers.
• The system's modular design allows for expansion to target additional biomarkers, increasing multiplexing capabilities.